Research on Public Opinion Monitoring System Based on Improved Fuzzy Controller

This paper proposes a novel network public opinion monitoring system that addresses the issue of traditional methods typically intervening only after the public opinion outbreak. The new system incorporates a self-adjusting weighted factor fuzzy controller. A closed-loop feedback public opinion monitoring system is formed by connecting an improved fuzzy controller with components such as a SVM emotion classifier. The system automatically processes different proportions of negative comments based on the controlled quantity—the proportion of negative comments; on the basis of traditional fuzzy controllers, two self-adjusting weighting factors are introduced to improve the system’s processing speed of public opinion. The experiment used a comment dataset to validate the effectiveness of the system and compared it with a system for monitoring public opinion using the basis of traditional fuzzy controllers. The experimental results showed that the system can operate effectively and achieve the expected public opinion processing effect; moreover, the processing speed of public opinion is superior to that of a conventional fuzzy controller-based public opinion monitoring system.